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Comprehensive Lifestyle Change To Prevent Breast Cancer

Comprehensive Lifestyle Change to Prevent Breast Cancer: A Feasibility Trial

Status
Active, not recruiting
Phases
Unknown
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT03448003
Enrollment
60
Registered
2018-02-27
Start date
2019-04-04
Completion date
2027-08-31
Last updated
2026-08-11

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Premenopausal

Brief summary

This trial studies how well comprehensive lifestyle change works in preventing patients from breast cancer. A program including dietary recommendations, physical activity, stress management and mindfulness training, learning sleep hygiene techniques, and behavioral counseling in addition to social support may help patients who may be at risk for breast cancer.

Detailed description

PRIMARY OBJECTIVES: I. Assess the feasibility of a randomized controlled trial involving a mobile, standardized, comprehensive integrative oncology (IO) prevention program. SECONDARY OBJECTIVES: I. Compare group differences over time in biological pathways including: immune function, gut microbiome, endocrine function, insulin and glucose metabolism, inflammation, other cancer-related pathways (from peripheral blood), antioxidant capacity, and nutrient levels. II. Determine whether the IO group has improved patient reported outcomes over time including: quality of life, sleep disturbances, aspects of mental health, and psychosocial measures including: mindfulness, social support, and measures of positive growth. III. Compare group differences over time in dietary patterns, fitness levels, percent body fat, and anthropometrics. OUTLINE: Patients are randomized into 1 of 2 groups. GROUP I: Patients attend IO prevention program consisting of 1-2 physical activity, nutrition and diet, and mind-body practice sessions over 60 minutes weekly for 12 weeks. Patients also attend a behavioral counseling session once weekly for up to 26 weeks. Patients complete exercises over 30-60 minutes 3-5 times weekly for 12 weeks. GROUP II: Patients receive no intervention. After 26 weeks, patients may crossover to Group I. After completion of study, patients are followed up at 26 weeks and 1 year.

Interventions

OTHERCancer Prevention

Attend IO prevention program

OTHERQuestionnaire Administration

Ancillary studies

Sponsors

M.D. Anderson Cancer Center
Lead SponsorOTHER
National Cancer Institute (NCI)
CollaboratorNIH

Study design

Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
PREVENTION
Masking
NONE

Eligibility

Sex/Gender
FEMALE
Age
18 Years to No maximum
Healthy volunteers
Yes

Inclusion criteria

* Able to read, write, and speak English * Premenopausal * A body mass index (BMI) \>= 25 * Have intact breasts and ovaries * Able to provide informed consent to participate in the study * Meet all the following criteria related to lifestyle: a) consume less than 3 servings of vegetables (excluding any fried servings) and 1 serving of fruit (not including juice)/day; b) engage in less than 150 minutes moderate/vigorous intensity activity per week, defined as anything that causes small increases in breathing or heart rate for a sustained amount of time (e.g., brisk walking, bicycling); c) engage in a mind-body practice less once per week * Able mentally and physically to participate in interventions in this study (Note: If there are one or more positive responses to the Physical Activity Readiness Questionnaire \[PARQ\], then a physician-release for exercise is required prior to obtaining consent) * Access to internet connection * Able to come to University of Texas (UT) MD Anderson for the orientation and assessment sessions

Exclusion criteria

* Any personal history of cancer, including ductal carcinoma in situ (DCIS) and not including non-melanoma skin cancers * Any major thought disorder (e.g., schizophrenia, dementia) * Communication barriers (e.g. hard of hearing) * Poorly or uncontrolled diabetes in the opinion of the physician(s) * Being pregnant or planning on becoming pregnant within the next year * Contemplating any new pharmacologic/hormonal or prophylactic surgical intervention for breast cancer prevention within the next year (Note: Individuals taking tamoxifen, arimidex or other hormonal prevention strategies at time of consent will be eligible)

Design outcomes

Primary

MeasureTime frameDescription
Treatment group compliance rateUp to 1 yearWill be defined as attending at least 50% of sessions during the intervention delivery weeks (first 26 weeks) in the integrative oncology (IO) group. Will calculate the rates, frequencies, and 90% CIs of means by group, as well as for the differences between intervention groups as applicable. Will also examine demographic factors such as age, marital status, number of children, and employment status as they related to feasibility in terms of consent, adherence to the intervention, and retention in the study.
Retention rateUp to 1 yearWill calculate the rates, frequencies, and 90% CIs of means by group, as well as for the differences between intervention groups as applicable. Will also examine demographic factors such as age, marital status, number of children, and employment status as they related to feasibility in terms of consent, adherence to the intervention, and retention in the study.
Consent rateUp to 1 yearWill calculate the rates, frequencies, and 90% confidence intervals (CIs) of means by group, as well as for the differences between intervention groups as applicable. Will also examine demographic factors such as age, marital status, number of children, and employment status as they related to feasibility in terms of consent, adherence to the intervention, and retention in the study.

Secondary

MeasureTime frameDescription
Group differences over time in dietary patternsUp to 1 yearWill first conduct extensive descriptive analyses on the data collected at baseline and at each follow-up. Descriptive statistics including 90% CIs will be computed for the relevant measures. Will examine distribution characteristics of the variables using box plots, histograms, scatter plots, and the Kolmogorov-Smirnov test of normality where appropriate. Distribution assumptions will be evaluated, and if indicated, normalizing transformations or robust procedures will be used. Will evaluate bivariate associations between the outcome measures and selected demographic and medical variables, including age, ethnicity, body mass index, and cancer history using Pearson product-moment correlation coefficients, chi-squared tests, or other methods where appropriate. Will use GLMM. Separate sets of analyses will be conducted for each criterion variable.
Group differences over time in fitness levelsUp to 1 yearWill first conduct extensive descriptive analyses on the data collected at baseline and at each follow-up. Descriptive statistics including 90% CIs will be computed for the relevant measures. Will examine distribution characteristics of the variables using box plots, histograms, scatter plots, and the Kolmogorov-Smirnov test of normality where appropriate. Distribution assumptions will be evaluated, and if indicated, normalizing transformations or robust procedures will be used. Will evaluate bivariate associations between the outcome measures and selected demographic and medical variables, including age, ethnicity, body mass index, and cancer history using Pearson product-moment correlation coefficients, chi-squared tests, or other methods where appropriate. Will use GLMM. Separate sets of analyses will be conducted for each criterion variable.
Group differences over time in anthropometricsUp to 1 yearWill first conduct extensive descriptive analyses on the data collected at baseline and at each follow-up. Descriptive statistics including 90% CIs will be computed for the relevant measures. Will examine distribution characteristics of the variables using box plots, histograms, scatter plots, and the Kolmogorov-Smirnov test of normality where appropriate. Distribution assumptions will be evaluated, and if indicated, normalizing transformations or robust procedures will be used. Will evaluate bivariate associations between the outcome measures and selected demographic and medical variables, including age, ethnicity, body mass index, and cancer history using Pearson product-moment correlation coefficients, chi-squared tests, or other methods where appropriate. Will use GLMM. Separate sets of analyses will be conducted for each criterion variable.
Group differences over time in percent body fatUp to 1 yearWill first conduct extensive descriptive analyses on the data collected at baseline and at each follow-up. Descriptive statistics including 90% CIs will be computed for the relevant measures. Will examine distribution characteristics of the variables using box plots, histograms, scatter plots, and the Kolmogorov-Smirnov test of normality where appropriate. Distribution assumptions will be evaluated, and if indicated, normalizing transformations or robust procedures will be used. Will evaluate bivariate associations between the outcome measures and selected demographic and medical variables, including age, ethnicity, body mass index, and cancer history using Pearson product-moment correlation coefficients, chi-squared tests, or other methods where appropriate. Will use GLMM. Separate sets of analyses will be conducted for each criterion variable.
Gut microbiomeUp to 1 yearSequence processing and analysis will be performed using specific software for comparison and analysis of microbial communities.
Group differences over time in biological pathwaysUp to 1 yearWill first conduct extensive descriptive analyses on the data collected at baseline and at each follow-up. Descriptive statistics including 90% CIs will be computed for the relevant measures. Will examine distribution characteristics of the variables using box plots, histograms, scatter plots, and the Kolmogorov-Smirnov test of normality where appropriate. Distribution assumptions will be evaluated, and if indicated, normalizing transformations or robust procedures will be used. Will evaluate bivariate associations between the outcome measures and selected demographic and medical variables, including age, ethnicity, body mass index, and cancer history using Pearson product-moment correlation coefficients, chi-squared tests, or other methods where appropriate. Will use generalized linear mixed model regression (GLMM). Separate sets of analyses will be conducted for each criterion variable.

Countries

United States

Contacts

PRINCIPAL_INVESTIGATORLorenzo Cohen

M.D. Anderson Cancer Center

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Aug 12, 2026